Using the Collaborative Cross to identify the role of host genetics in defining the murine gut microbiome

Abstract

Background: The human gut microbiota is a complex community comprised of trillions of bacteria and is critical for the digestion and absorption of nutrients. Bacterial communities of the intestinal microbiota influence the development of several conditions and diseases. We studied the effect of host genetics on gut microbial composition using Collaborative Cross (CC) mice, a panel of genetically diverse mouse strains. CC mice are genetically diverse across strains, but genetically identical within a given strain allowing for repetition and deeper analysis than is possible with other collections of genetically diverse mice. Results: 16S rRNA from the feces of 167 mice from 28 different CC strains was sequenced and analyzed using the Qiime2 pipeline. We observed large variance in the bacterial composition across CC strains starting at the phylum level. Using bacterial composition data, we identified 26 significant Quantitative Trait Locus (QTL) linked to 23 genera on 15 different mouse chromosomes. Genes within these intervals were analyzed for significant association with pathways and the previously known human GWAS database using Enrichr and DAVID analysis. Multiple host genes involved in obesity, glucose homeostasis, immunity, neurological diseases, and many other protein-coding genes located in these regions may play roles in determining the composition of the gut microbiota. After the collection of feces used for sequencing, a subset of CC mice was infected with Salmonella Typhimurium. Using the infection outcome data, we correlated the increase in abundance of Genus Lachnospiraceae and decrease in Genus Parasutterella to positive health outcomes after infection. Machine learning classifiers accurately predicted the CC strain and the infection outcome using pre-infection bacterial composition data from the feces. Conclusion: Our study supports the hypothesis that multiple host genes influence the gut microbiome composition and homeostasis, and that certain organisms may influence health outcomes after S. Typhimurium infection.

Antibiotic treatment induces microbiome dysbiosis and reduction of neuroinflammation following traumatic brain injury in mice

“…This aligns with previous studies that suggest a positive correlation between Lachnospiraceae UCG-006 and antioxidant enzyme activity [43]. A higher relative abundance of the genus Lachnospiraceae UCG-006 is associated with positive health outcomes after infection with S. Typhimurium [32]. Thus, the increase in this genus could suggest its contribution to repair processes after TBI, potentially lessening inflammation and enhancing recovery.…”

“…Samples were quality filtered, demultiplexed, and prepared for downstream processing using sdm. Taxonomic alignment to the ‘Silva 138.1 prokaryotic SSU’ was performed using the RDPclassifer [32]. OTUs were clustered using VSEARCH and a final phylogenetic tree was constructed from a MAFFT multiple sequence alignment using FastTree2 [33–35].…”

Antibiotic treatment induces microbiome dysbiosis and reduction of neuroinflammation following traumatic brain injury in mice

“…Samples were quality ltered, demultiplexed, and prepared for downstream processing using sdm. Taxonomic alignment to the 'Silva 138.1 prokaryotic SSU' was performed using the RDPclassifer [32]. OTUs were clustered using VSEARCH and a nal phylogenetic tree was constructed from a MAFFT multiple sequence alignment using FastTree2 [33][34][35].…”

Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistantStaphylococcus aureusUSA300

“…Mice were fed Envigo Teklad Global 19% Protein Extrudent Rodent Diet (2919) or Envigo Teklad Rodent Diet (8604) based on strain need. Mice were provided with cardboard huts, food, and water ad libitum [143].…”

“…V E and V G are the variance explained by the environmental and the genetic component respectively while V P is the total phenotypic variance for a given phenotype. Detailed explanation of the calculation can be found here [116].…”